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EP4298605A4 - ONLINE TRAINING-BASED ENCODER TUNING WITH MULTI-MODEL SELECTION IN NEURAL IMAGE COMPRESSION - Google Patents

ONLINE TRAINING-BASED ENCODER TUNING WITH MULTI-MODEL SELECTION IN NEURAL IMAGE COMPRESSION Download PDF

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Publication number
EP4298605A4
EP4298605A4 EP23773160.9A EP23773160A EP4298605A4 EP 4298605 A4 EP4298605 A4 EP 4298605A4 EP 23773160 A EP23773160 A EP 23773160A EP 4298605 A4 EP4298605 A4 EP 4298605A4
Authority
EP
European Patent Office
Prior art keywords
image compression
model selection
online training
based encoder
neural image
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP23773160.9A
Other languages
German (de)
French (fr)
Other versions
EP4298605A1 (en
Inventor
Ding DING
Xiaozhong Xu
Shan Liu
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tencent America LLC
Original Assignee
Tencent America LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tencent America LLC filed Critical Tencent America LLC
Publication of EP4298605A1 publication Critical patent/EP4298605A1/en
Publication of EP4298605A4 publication Critical patent/EP4298605A4/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00Image coding
    • G06T9/002Image coding using neural networks
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/103Selection of coding mode or of prediction mode
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146Data rate or code amount at the encoder output
    • H04N19/149Data rate or code amount at the encoder output by estimating the code amount by means of a model, e.g. mathematical model or statistical model
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/172Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/46Embedding additional information in the video signal during the compression process

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Algebra (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Compression Of Band Width Or Redundancy In Fax (AREA)
  • Image Analysis (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)
EP23773160.9A 2022-03-29 2023-03-23 ONLINE TRAINING-BASED ENCODER TUNING WITH MULTI-MODEL SELECTION IN NEURAL IMAGE COMPRESSION Pending EP4298605A4 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US202263325115P 2022-03-29 2022-03-29
US18/122,651 US20230316588A1 (en) 2022-03-29 2023-03-16 Online training-based encoder tuning with multi model selection in neural image compression
PCT/US2023/016042 WO2023192096A1 (en) 2022-03-29 2023-03-23 Online training-based encoder tuning with multi model selection in neural image compression

Publications (2)

Publication Number Publication Date
EP4298605A1 EP4298605A1 (en) 2024-01-03
EP4298605A4 true EP4298605A4 (en) 2024-07-17

Family

ID=88193200

Family Applications (1)

Application Number Title Priority Date Filing Date
EP23773160.9A Pending EP4298605A4 (en) 2022-03-29 2023-03-23 ONLINE TRAINING-BASED ENCODER TUNING WITH MULTI-MODEL SELECTION IN NEURAL IMAGE COMPRESSION

Country Status (4)

Country Link
US (1) US20230316588A1 (en)
EP (1) EP4298605A4 (en)
CN (1) CN117461055A (en)
WO (1) WO2023192096A1 (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2025160707A1 (en) * 2024-01-29 2025-08-07 Intel Corporation Intelligent ai generated video guided by hardware encoder
CN119342214B (en) * 2024-12-20 2025-03-11 国网安徽省电力有限公司电力科学研究院 Image coding and decoding model training method and system based on deviation control

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020008104A1 (en) * 2018-07-02 2020-01-09 Nokia Technologies Oy A method, an apparatus and a computer program product for image compression
US11842531B2 (en) * 2020-02-28 2023-12-12 United States Postal Service System and method for image compression
US12058348B2 (en) * 2020-04-17 2024-08-06 Qualcomm Incorporated Parallelized rate-distortion optimized quantization using deep learning
EP4144087A1 (en) * 2020-04-29 2023-03-08 Deep Render Ltd Image compression and decoding, video compression and decoding: methods and systems

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
GUO LU ET AL: "Content Adaptive and Error Propagation Aware Deep Video Compression", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 25 March 2020 (2020-03-25), XP081629309 *
JIAHENG LIU ET AL: "A Unified End-to-End Framework for Efficient Deep Image Compression", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 24 May 2020 (2020-05-24), XP081660636 *
NANNAN ZOU ET AL: "Learning to Learn to Compress", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 1 May 2021 (2021-05-01), XP081950101 *
See also references of WO2023192096A1 *
WANG YEFEI ET AL: "Ensemble Learning-Based Rate-Distortion Optimization for End-to-End Image Compression", IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, IEEE, USA, vol. 31, no. 3, 5 June 2020 (2020-06-05), pages 1193 - 1207, XP011843402, ISSN: 1051-8215, [retrieved on 20210304], DOI: 10.1109/TCSVT.2020.3000331 *

Also Published As

Publication number Publication date
WO2023192096A1 (en) 2023-10-05
CN117461055A (en) 2024-01-26
US20230316588A1 (en) 2023-10-05
EP4298605A1 (en) 2024-01-03

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